get_call_graph

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions 'generates a call graph', implying a read-only analysis operation, but fails to detail aspects like performance impact, error handling, or output format. This leaves significant gaps in understanding how the tool behaves beyond its basic purpose.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, efficient sentence that directly states the tool's purpose without unnecessary words. It is appropriately sized and front-loaded, making it easy to parse, though it could benefit from more detail given the lack of annotations and schema coverage.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the complexity of generating a call graph, no annotations, no output schema, and low schema coverage, the description is incomplete. It does not address key aspects like what the output contains, how to interpret results, or any limitations, making it inadequate for effective tool use by an AI agent.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has 0% description coverage, so parameters 'symbolName', 'moduleId', and 'scanAllModules' are undocumented. The description does not add any meaning beyond the schema, such as explaining what a 'symbolName' represents or the effect of 'scanAllModules', failing to compensate for the low coverage.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description states the tool 'generates a call graph for a specific function', which provides a clear verb ('generates') and resource ('call graph') with a scope ('for a specific function'). However, it does not differentiate from sibling tools like 'analyze_structure' or 'list_functions', which might have overlapping purposes in code analysis, leaving the distinction vague.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description offers no guidance on when to use this tool versus alternatives. It lacks context on prerequisites, such as needing a function symbol and module, or exclusions, like when other tools might be more appropriate for broader analysis or listing functions, leaving the agent without usage direction.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.